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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 李學智 | |
dc.contributor.author | Po-Ying Chen | en |
dc.contributor.author | 陳柏穎 | zh_TW |
dc.date.accessioned | 2021-06-13T03:38:49Z | - |
dc.date.available | 2006-07-31 | |
dc.date.copyright | 2006-07-31 | |
dc.date.issued | 2006 | |
dc.date.submitted | 2006-07-25 | |
dc.identifier.citation | [1] S. Roy, J. R. Foerster, V. S. Somayazulu, and D. G. Leeper, “Ultrawideband radio design: the promise high-speed, short-range wireless connectivity,” Proc. IEEE, vol. 92, pp. 295-311, Feb. 2004.
[2] E. Telatar, “Capacity of multi-antenna Gaussian channels,” Euro. Trans. Commun., vol. 10, pp. 585-595, Nov.-Dec. 1999. [3] J. C. Liberti and T. S. Rappaport, Smart Antennas for Wireless Communications: IS-95 and Third Generation CDMA Applications, New Jersey: Prentice Hall, 1999. [4] K. E. Baddour and N. C. Beaulieu, “Accurate simulation of multiple cross-correlated fading channels,” in Proc. IEEE ICC’02, pp. 267-271, 2002. [5] A. Paulraj, R. Nabar, D. Gore, Introduction to Space-Time Wireless Communications, Cambridge University Press, 2003. [6] W. C. Jakes, Microwave Mobile Communications. New York: Wiley, 1974, pp. 60–65. [7] W. C. Y. Lee, Mobile Communications Engineering. McGraw Hill Publications, NY, 1982. [8] J. Salz and J. H. Winters, “Effect of fading correlation on adaptive arrays in digital wireless communications,” in Proc. IEEE Vehicular Technology Conf., vol. 3, 1993, pp. 1758–1774. [9] J. Fuhl, A. F. Molisch, and E. Bonek, “Unified channel model for mobile radio systems with smart antennas,” Proc. Inst. Elect. Eng. Radar, Sonar Navig., vol. 145, no. 1, pp. 32–41, Feb. 1998. [10] D. S. Shiu, G. J. Foschini, M. J. Gans, and J. M. Kahn, “Fading correlation and its effect on the capacity of multi-element antenna systems,” IEEE Trans. Commun., vol. 48, pp. 502-513, Mar. 2000. [11] T. A. Chen, M. P. Fitz, W. Y. Kuo, M. D. Zoltowski, and J. H. Grimm, “A space-time model for frequency nonselective Rayleigh fading channels with applications to space-time modems,” IEEE J. Select. Areas Commun., vol. 18, pp. 1175–1190, July 2000. [12] Shiu D-S, Wireless Communication Using Dual Antenna Arrays, Kluwer Academic Publishers: Norwell, MA, 2000. [13] J. S. Sadowsky and V. Kafedziski, “On the correlation and scattering functions of the WSSUS channel for mobile communication,” IEEE Trans. Veh. Technol., vol. 47, pp. 270–282, Feb. 1998. [14] M. Patzold, U. Killat, Y. Li, and F. Laue, “Modeling, analysis, and simulation of nonfrequency-selective mobile radio channels with asymmetrical Doppler power spectral density shapes,” IEEE Trans. Veh. Technol., vol. 46, pp. 494–507, May 1997. [15] W. R. Braun and U. Dersch, “A physical mobile radio channel model,” IEEE Trans. Veh. Technol., vol. 40, pp. 472–482, May 1991. [16] Q. Spencer, M. Rice, B. Jeffs, and M. Jensen, “A statistical model for angle of arrival in indoor multipath propagation,” in Proc. IEEE Vehicular Technology Conf., Phoenix, AZ, 1997, pp. 1415–1419. [17] J. G. Wang, A. S. Mohan, and T. A. Aubrey, “Angles-of- arrival of multipath signals in indoor environments,” in Proc. IEEE Vehicular Technology Conf., Atlanta, GA, 1996, pp. 155–159. [18] S. Guerin, “Indoor wideband and narrowband propagation measurements around 60.5 GHz in an empty and furnished room,” in Proc. IEEE Vehicular Technology Conf., Atlanta, GA, 1996, pp. 160–164. [19] W. C.Y. Lee, “Finding the approximate angular probability density function of wave arrival by using a directional antenna,” IEEE Trans. Antennas Propagat., vol. AP-21, pp. 328–334, May 1973. [20] A. Abdi, J. A. Barger, and M. Kaveh, “A parametric model for the distribution of the angle of arrival and the associated correlation function and power spectrum at the mobile station,” IEEE Trans. Veh. Technol., vol. 51, pp. 425-434, May 2002. [21] A. Abdi and M. Kaveh, “A space-time correlation model for multielement antenna systems in mobile fading channels,” IEEE J. Select. Areas Commun., vol. 20, pp. 550-560, Apr. 2002. [22] G. J. Byers and F. Takawira, “Spatially and temporally correlated MIMO channels: modeling and capacity analysis,” IEEE Trans. Veh. Technol., vol. 53, pp. 634-643, May 2004. [23] P. Petrus, J. H. Reed, and T. S. Rappaport, “Effects of directional antennas at the base station on the Doppler spectrum,” IEEE Commun. Lett., vol. 1, pp. 40-42, Mar. 1997. [24] J. C. Libert and T. S. Rappaport, “A geometrically based model for line of sight multipath radio channels,” in Proc. IEEE Vehicular Technology Conf., pp. 844–848, Apr. 1996. [25] C. Oestges, V. Erceg and A. J. Paulraj, “A physical scattering model for MIMO macrocellular broadband wireless channels,” IEEE J. Select. Areas Commun., vol. 21, pp. 721-729, June 2003. [26] D. Gesbert, H. Bolcskei, D. A. Gore, and A. J. Paulraj, “Outdoor MIMO wireless channels: models and performance prediction,” IEEE Trans. Commun., vol. 50, pp. 1926-1934, Dec. 2002. [27] D. Chizhik, G. J. Foschini, M. J. Gans, and R. A. Valenzuela, “Keyholes, correlations, and capacities of multielement transmit and receive antennas,” IEEE Trans. Wireless Commun., vol. 1, pp. 361-368, April 2002. [28] A. A. M. Saleh and R. A. Valenzuela, “A statistical model for indoor multipath propagation,” IEEE J. Select. Area Commun., vol. SAC-5, pp.128-137, Feb. 1987. [29] Q. H. Spencer, B. D. Jeffs, M. A. Jensen and A. L. Swindlehurst, “Modeling the statistical time and angle of arrival characteristics of an indoor multipath channel,” IEEE J. Select. Area Commun, vol. 18, pp. 347-360, March 2000. [30] J. W. Wallace and M. A. Jensen, “Modeling the indoor MIMO wireless channel,” IEEE Trans. Antennas Propagat., vol. 50, pp. 591-599, May 2002. [31] A. F. Molisch, J. R. Foerster, and M. Pendergrass, “Channel models for ultrawideband personal area networks,” IEEE Wireless Commun. Mag., vol. 10, pp. 14-21, Dec. 2003. [32] K. Yu and B. Ottersten, “Models for MIMO propagation channels: a review,” J. Wirel. Commun. Mob. Comput., vol. 2, pp. 653-666, 2002. [33] J. P. Kermoal, L. Schumacher, P. E. Mogensen, and K. I. Pedersen, “Experimental investigation of correlation properties of MIMO radio channels for indoor picocell scenarios,” in Proc. IEEE Vehicular Technology Conf., 2000; pp. 14–21. [34] K. I. Pedersen, J. B. Andersen, J. P. Kermoal, P. E. Mogensen, “A stochastic multiple-input multiple-output radio channel model for evaluation of space-time coding algorithms,” in Proc. IEEE Vehicular Technology Conf., 2000; pp. 893–897. [35] D. P. McNamara, M. A. Beach, P. N. Fletcher, P. Karlsson, “Initial investigation of multiple-input multiple-output channels in indoor environments,” in Proc. IEEE Benelux Chapter Symposium on Communications and Vehicular Technology, Leuven, Belgium, Oct. 2000. [36] K. Yu, M. Bengtsson, B. Ottersten, P. Karlsson, D. McNamara, and M. Beach, “Measurement analysis of NLOS indoor MIMO channels,” in Proc. IST Mobile Communications Summit, Barcelona, Spain, Sept. 2001; pp. 277–282. [37] K. Yu, M. Bengtsson, B. Ottersten, D. McNamara, P. Karlsson, and M. Beach, “Second order statistics of NLOS indoor MIMO channels based on 5.2 GHz measurements,” in Proc. IEEE Globecom, Nov. 2001, pp. 156–160. [38] 3rd Generation Partnership Project Technical Report, TR. 25.876, “Multiple input multiple output (MIMO) antennae in UTRA,” 2004. [39] 3rd Generation Partnership Project Technical Report, TR. 25.996, “Spatial channel model for multiple input multiple output (MIMO) simulations,” 2003. [40] IEEE 802 11-03/161r2, TGn Indoor MIMO WLAN Channel Models, 2004. [41] R. J. -M. Cramer, R. A. Scholtz, and M. Z. Win, “Evaluation of an ultra-wide-band propagation channel,” IEEE Trans. Antennas Propagat., vol. 50, pp. 561-570, May 2002. [42] L. Schumacher “WLAN MIMO Channel Matlab program,” download information: http://www.info.fundp.ac.be/~lsc/Research/IEEE_80211_HTSG_CMSC/distribution_terms.html. [43] R. B. Ertel, P. Cardieri, K. W. Sowerby, T. S. Rappaport, JH Reed, “Overview of spatial channel models for antenna array communication systems,” IEEE Personal Commun. Mag., vol. 5, pp. 10-22, Feb. 1998. [44] A. Stéphenne and B. Champagne, “Effective multi-path vector channel simulator for antenna array systems,” IEEE Trans. Veh. Technol., vol. 49, pp. 2370-2381, Nov. 2000. [45] Z. Latinovic, A. Abdi, and Y Bar-Ness, “A wideband space-time model for MIMO mobile fading channels,” in Proc. IEEE WCNC’03, pp. 338-342, 2003. [46] K. E. Baddour and N. C. Beaulieu, “Autoregressive models for fading channel simulation,” in Proc. IEEE Globecom 2001, pp. 1187-1192, Nov. 2001. [47] K. E. Baddour and N. C. Beaulieu, “Autoregressive models for fading channel simulation,” IEEE Trans. Wireless Commun., vol. 4, pp. 1650-1662, July 2005. [48] 3rd Generation Partnership Project Technical specification, “Spreading and modulation (FDD) (Release 6),” 3GPP TS 25.213 V6.0.0, 2003. [49] 3rd Generation Partnership Project Technical specification “Physical layer procedure (FDD) (Release 6),”, 3GPP TS 25.214 V6.2.0, 2004. [50] S. Alamouti, “A simple transmit diversity technique for wireless communications,” IEEE J. Select. Areas Commun., vol. 16, pp. 1451-1458, Oct. 1998. [51] B. A. Bjerke, Z. Zvonar, J. G. Proakis, “Antenna diversity combining schemes for WCDMA systems in fading multipath channels,” IEEE Trans. Wireless Commun., vol. 3, pp. 97-106, Jan. 2004. [52] D. Cassioli, M. Z. Win, and A. F. Molisch, “The ultra-wide bandwidth indoor channel: from statistical model to simulations,” IEEE J. Select. Area Commun, vol. 20, pp. 1247-1257, Aug. 2002. [53] J. Kunisch, E. Zollinger, J. Pamp, and A. Winkelmann, “MEDIAN 60 GHz wideband indoor radio channel measurements and model,” in Proc. IEEE Vehicular Technology Conf., 1999, pp. 2393–2397. [54] BroadWAY WP1D2, “Functional system parameter description,” 2002. [55] R. A. Andrews, P. P. Mitra, and R. de Carvalho, “Tripling the capacity of wireless communications using electromagnetic polarization,” Nature, vol. 409, pp. 316–318, Jan. 2001. [56] V. Erceg, P. Soma, D. S. Baum, and S. Cartreux, “Multiple-input multiple-output fixed wireless radio channel measurements and modeling using dual-polarized antennas at 2.5 GHz,” IEEE Trans. Wireless Commun., vol. 3, pp. 2288-2298, Nov. 2004. [57] V. Erceg, H. Sampath, and S Catreux, “Dual-polarization versus single-polarization MIMO channel measurement results and modeling,” IEEE Trans. Wireless Commun., vol. 5, pp. 28-33, Jan. 2006. [58] C. Oestges, V. Erceg, and A. J. Paulraj, “Propagation modeling of MIMO multipolarized fixed wireless channels,” IEEE Trans. Veh. Technol., vol. 53, pp. 644-654, May 2004. [59] T. Eyceoz, A. Duel-Hallen, and H. Hallen, “Deterministic channel modeling and long range prediction of fast fading mobile radio channels,” IEEE Commun. Lett., vol. 2, pp. 254-256, Sep. 1998. [60] A. Duel-Hallen, S. Hu, and H. Hallen, “Long-range prediction of fading signals,” IEEE Signal Processing Mag., pp. 62-75, May 2000. [61] S. Guncavdi and A. Duel-Hallen, “Performance analysis of space-time transmitter diversity techniques for WCDMA using long range prediction,” IEEE Trans. Wireless Commun., vol. 4, pp. 40-45, Jan. 2005. [62] D. Schafhuber and G. Martz, “MMSE and adaptive prediction of time-varying channels for OFDM systems,” IEEE Trans. Wireless Commun., vol. 4, pp. 593-602, Mar. 2005. [63] H. Stark and J. W. Woods, Probability, Random Processes, and Estimation Theory for Engineers, 2nd Edition, Prentice Hall, 1994. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/32248 | - |
dc.description.abstract | 隨著無線通訊多媒體服務的需求遽增,提供高速傳輸成為系統業者責無旁貸的任務。最近,多輸入多輸出傳輸技術已被證明,相對於傳統單一輸入單一輸出系統,它可以大幅提升系統容量。除了來自於空間分集的效能提升和傳輸距離的改善,這項技術利用多路徑傳播的特性,建立平行的等效通道來傳送資料,因而使系統在有限頻寬下,大大地提升傳輸速率。由於它的效能改善以及較高的頻譜使用效率,因此無論在行動通訊系統(3G Long Term Evolution)抑或無線區域網路(IEEE 802.11n),皆將多輸入多輸出技術納入下一代之傳輸標準。
有線與無線通訊最大的差異在於通道的不同。在無線通訊系統中,通道對於傳輸效能之優劣扮演了相當關鍵的角色。因此,掌握無線環境中的通道特性成為一項重要的課題。傳統上,單一輸入單一輸出的通道可以被兩個維度的統計特性所描述,即時域和頻域;而當我們考慮多天線系統架構時,第三個維度—亦即空間—上的通道特徵則成為另一項我們不可忽略且必須了解的因素。 一個精確的通道模型不僅幫助我們進一步透析無線電傳播的性質,並且它還能提供評估、甚至預測系統效能的方法。本論文將概要的介紹一些在文獻上已被提出的空間通道模型,並且完整地分析室內和室外多輸入多輸出通道的統計特性,另外還提出幾種較有效率的方法來產生多輸入多輸出通道。藉由通道模型的分析探討,我們能較容易地找出系統效能下降的原因,從而設計強健的傳送接收機來抵抗通道衰落或干擾。 | zh_TW |
dc.description.abstract | As the demand on wireless multi-media increases, it becomes indispensable for service providers to provide high-data-rate transmissions. Recently, multiple-input multiple-output (MIMO) technology is shown to have tremendous capacity enhancement over single-input single-output (SISO) systems. This technique gains from spatial diversity and increases transmission range. It also exploits multipath propagation to create parallel channels to convey information, and thereby the data rate is increased without consuming extra radio frequency. Due to its compelling performance enhancement and high spectral efficiency, the MIMO technology has been adopted by different wireless communications standards, no matter in cellular systems (3G Long Term Evolution) or in wireless local area networks (IEEE 802.11n task group).
The greatest difference between wired and wireless communications lies on the channel. In wireless communication systems, channels play an important role on transmission performance. Therefore, it is essential for us to know well the channel behaviors in a wireless environment. Traditionally, the SISO channel is described by the statistics along two dimensions: time and frequency. As the multi-antenna technology is taken into account, to capture the additional characteristics along the third dimension—space—is necessary. Modeling the channel accurately can not only help us gain more insights about radio propagation but also provides an approach to evaluate or even predict system performance. This thesis gives an overview of spatial channel models developed in literature, and thoroughly analyzes the statistical behaviors of indoor and outdoor MIMO channels. We also propose several methods to generate MIMO channels more efficiently. By means of channel understanding, it will become easier to find out the causes of performance degradation and thereby design a robust transceiver to combat fading and interferences. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T03:38:49Z (GMT). No. of bitstreams: 1 ntu-95-F90942068-1.pdf: 2656909 bytes, checksum: d2ea4b42eeb64c278a033e69da6910a2 (MD5) Previous issue date: 2006 | en |
dc.description.tableofcontents | Abstract I
Contents III List of Figures VII List of Tables XI Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Thesis Overview 2 Chapter 2 Overview of Spatial Channel Models 5 2.1 Preliminaries of MIMO Channels 5 2.2 Geometry-Based Channel Models 7 2.2.1 One-Ring and Two-Ring Models 8 2.2.2 GBSBCM and GBSBEM 11 2.2.3 Combined Elliptical Ring Model 14 2.3 Distributed Scattering Model 15 2.4 Saleh-Valenzuela Model with AOA/AOD 18 2.5 Measurement-Based Channel Model 20 2.6 MIMO Channel Models in Standards 23 2.6.1 Spatial Channel Model for MIMO Simulations in 3G Cellular Systems 24 2.6.2 MIMO Channel Models in WLAN Systems 29 2.7 Summary 33 Chapter 3 Outdoor MIMO Channel Modeling 35 3.1 Introduction 35 3.2 Space-Time Correlation for MIMO Fading Signals 36 3.2.1 STC for NB Fading Signals in Macrocells 39 3.2.2 STC for NB Fading Signals in Microcells 40 3.2.3 STC for WB Fading Signals in Microcells 41 3.2.4 STC for WB Fading Signals in Macrocells 42 3.3 Generation of MIMO Fading Signals 43 3.4 Multiple Clusters in Macrocells 48 3.5 Simulations, Verification and Applications 50 3.5.1 Space-Time Correlations of MIMO Channels 51 3.5.2 Outdoor MIMO Capacity 59 3.5.3 Performance of DL-WCDMA with Tx. and Rx. Diversity 64 3.6 Summary 67 Chapter 4 Indoor NLOS MIMO Channel Modeling and Generation 69 4.1 Introduction 69 4.2 The NLOS Indoor Multipath Channel Model 70 4.3 Statistics for NLOS Indoor Channels 73 4.3.1 RMS Delay Spread 73 4.3.2 Space-Frequency Correlation 74 4.4 Efficient Channel Generation Methods 75 4.4.1 Autoregressive and Spatial Filtering (ARSF) Method 75 4.4.2 Convolution Method 78 4.5 Simulations, Verification and Comparison 81 4.6 Summary 89 Chapter 5 Indoor LOS MIMO Channel Modeling and Verification 91 5.1 Introduction 91 5.2 The LOS Indoor Multipath Channel Model 94 5.3 Statistics for LOS Indoor Channels 97 5.3.1 RMS Delay Spread 97 5.3.2 Space-Frequency Correlation 102 5.4 Generation of Indoor LOS Channels 103 5.5 Comparison with Measurement Data 108 5.6 Indoor MIMO Capacity 116 5.7 Summary 120 Chapter 6 Conclusion 123 6.1 Summary of This Thesis 123 6.2 Future Works 125 Appendix 127 Appendix I 127 Appendix II 132 Appendix III 133 Appendix IV 136 Appendix V 138 Appendix VI 141 References 145 Abbreviations 151 Author’s Publications 153 | |
dc.language.iso | en | |
dc.title | 多輸入多輸出通道之分析探討及其在無線通訊領域之應用 | zh_TW |
dc.title | Multiple-Input Multiple-Output (MIMO) Channel Understanding and Its Applications to Wireless Communications | en |
dc.type | Thesis | |
dc.date.schoolyear | 94-2 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 李大嵩,吳靜雄,林丁丙,唐震寰,許大山,陳光禎,闕志達 | |
dc.subject.keyword | 多輸入多輸出,多路徑傳播,通道模型,通道認知,通道產生,通道量測,空時相關函數,空頻相關函數,多輸入多輸出通道容量, | zh_TW |
dc.subject.keyword | Multiple-input multiple-output (MIMO),multipath propagation,channel modeling,channel understanding,channel generation,channel measurement,space-time correlation function,space-frequency correlation function,MIMO capacity, | en |
dc.relation.page | 154 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2006-07-27 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
顯示於系所單位: | 電信工程學研究所 |
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